Objectives

The goal of this step in the workflow is to compare S2 streamflow height to precipitation data in order to quality check the streamflow data.

Set Up

  • Install/load necessary R packages

  • Set working directory if necessary (or create a file path to use throughout the RMD to call the data from Box)

  • Read in water year data from CSVs in the intermediate_data directory

#read in necessary CSV files from prior RMDs
all_streamflow <- read_csv(here("intermediate_data", "all_streamflow.csv"))
air_temp_30_clean <- read_csv(here("intermediate_data", "air_temp_30_clean.csv"))
bogwell_clean <- read_csv(here("intermediate_data", "bogwell_clean.csv")) 
mc_clean <- read_csv(here("intermediate_data", "mc_clean.csv")) %>% 
  rename(datetime = collected)
precip_15_clean <- read_csv(here("intermediate_data", "precip_15_clean.csv")) 
precip_6h_clean <- read_csv(here("intermediate_data", "precip_6h_clean.csv")) 
precip_12h_clean <- read_csv(here("intermediate_data", "precip_12h_clean.csv")) 
precip_daily_clean <- read_csv(here("intermediate_data", "precip_daily_clean.csv")) 
se_clean <- read_csv(here("intermediate_data", "se_clean.csv"))
  • Set constant values
#set constants 
min_year = 2017
max_year = 2021

Streamflow compared to cumulative precipitation and manual checkpoints

For interactive plots,

  • cumulative precipitation is plotted as grey bars,

  • streamflow is plotted as a blue line,

  • and streamflow manual checkpoints are plotted as black dots.

Cumulative Precipitation Every 6 Hours

#calculate the ratio of the 2 y-axes to plot the variables together
trans_value <- max(precip_6h_clean$precip_10_in, na.rm = TRUE) / max(all_streamflow$stream_height_ft, na.rm = TRUE)

#plot 
p_6h <- ggplot() + 
  #precipitation data 
  geom_col(data = precip_6h_clean, 
            aes(x = datetime, 
                y = precip_10_in,
                group = 1,
                #create hovering labels for interactive graph 
                text = paste0("DateTime: ", datetime, "\n",
                              "Precipitation (in/10): ", precip_10_in)),
            colour = I("grey"),
            size = 0.25) + 
  #streamflow data 
  geom_line(data = all_streamflow,
             aes(x = datetime, 
                 y = stream_height_ft, 
                 group = 1,
                 #create hovering labels for interactive graph 
                 text = paste0("DateTime: ", datetime, "\n",
                              "Stream Height (ft): ", round(stream_height_ft, digits = 3))),
            color = "blue",
            size = 0.4) + 
  #manual check points
  geom_point(data = mc_clean, 
             aes(x = datetime, 
                 y = stripchart_stage, 
                 group = 1,
                 #create hovering labels for interactive graph 
                 text = paste0("DateTime: ", datetime, "\n",
                              "Stream Height Checkpoint (ft): ", stripchart_stage)),
             size = 0.5) + 
  theme_classic() + 
  labs(x = "Time", 
       title = paste0("S2 Bog Streamflow and Cumulative \n Precipitation Every 6 Hours (", min_year, "-", max_year, ")"),
       subtitle = "Streamflow is plotted in blue. \n Precipitation is plotted in grey. \n Manual streamflow checks are plotted as black points.") + 
  theme(plot.title = element_text(hjust = 0.5),
        plot.subtitle = element_text(hjust = 0.5, 
                                     size = 7)) +
  scale_y_continuous(
    #features of the first axis
    name = "Stream Height (ft)",
    #add a second axis and specify its features
    ##determine the ratio between the max value of Axis 1 vs the max value of Axis 2 to decide what number to put in the trans argument
    sec.axis = sec_axis(trans = ~.*trans_value, name = "Cumulative Precipitation / 10 (in)")
  )

#static plot
#p_6h

#save the plot in the figures folder 
ggsave(filename = "streamflow_precip_6h_mc.png",
       plot = p_6h,
       path = "figures/",
       width = 8,
       height = 4,
       units = c("in"),
       dpi = 300)

#interactive plot 
ggplotly(p_6h, tooltip = "text") %>% 
  layout(title = list(text = paste0(paste0("S2 Bog Streamflow and Cumulative \n Precipitation Every 6 Hours (", min_year, "-", max_year, ")"),
                                    '<br>',
                                    '<sup>',
                                     paste0(" "), 
                                    '</sup>')), 
         font = list(size = 12)
         )

Cumulative Precipitation Every 12 Hours

For interactive plots,

  • cumulative precipitation is plotted as grey bars,

  • streamflow is plotted as a blue line,

  • and streamflow manual checkpoints are plotted as black dots.

#calculate the ratio of the 2 y-axes to plot the variables together
trans_value <- max(precip_12h_clean$precip_10_in, na.rm = TRUE) / max(all_streamflow$stream_height_ft, na.rm = TRUE)

#plot 
p_12h <- ggplot() + 
  #precipitation data 
  geom_col(data = precip_12h_clean, 
            aes(x = datetime, 
                y = precip_10_in, 
                group = 1,
                #create hovering labels for interactive graph 
                text = paste0("DateTime: ", datetime, "\n",
                              "Precipitation (in/10): ", precip_10_in)),
            colour = I("grey"),
            size = 0.25) + 
  #streamflow data 
  geom_line(data = all_streamflow,
             aes(x = datetime, 
                 y = stream_height_ft, 
                 group = 1,
                 #create hovering labels for interactive graph 
                 text = paste0("DateTime: ", datetime, "\n",
                              "Stream Height (ft): ", round(stream_height_ft, digits = 3))),
            color = "blue",
            size = 0.4) + 
  #manual check points
  geom_point(data = mc_clean, 
             aes(x = datetime, 
                 y = stripchart_stage, 
                 group = 1,
                 #create hovering labels for interactive graph 
                 text = paste0("DateTime: ", datetime, "\n",
                              "Stream Height Checkpoint (ft): ", stripchart_stage)),
             size = 0.5) + 
  theme_classic() + 
  labs(x = "Time", 
       title = paste0("S2 Bog Streamflow and Cumulative \n Precipitation Every 12 Hours (", min_year, "-", max_year, ")"),
       subtitle = "Streamflow is plotted in blue. \n Precipitation is plotted in grey. \n Manual streamflow checks are plotted as black points.") + 
  theme(plot.title = element_text(hjust = 0.5),
        plot.subtitle = element_text(hjust = 0.5, 
                                     size = 7)) +
  scale_y_continuous(
    #features of the first axis
    name = "Stream Height (ft)",
    #add a second axis and specify its features
    ##determine the ratio between the max value of Axis 1 vs the max value of Axis 2 to decide what number to put in the trans argument
    ###for example, max value of precipitation / max value of streamflow = 0.533...
    sec.axis = sec_axis(trans = ~.*trans_value, name = "Cumulative Precipitation / 10 (in)")
  )

#static plot
#p_12h

#save the plot in the figures folder 
ggsave(filename = "streamflow_precip_12h_mc.png",
       plot = p_12h,
       path = "figures/",
       width = 8,
       height = 4,
       units = c("in"),
       dpi = 300)

#interactive plot 
ggplotly(p_12h, tooltip = "text")

Cumulative Daily Precipitation

For interactive plots,

  • cumulative precipitation is plotted as grey bars,

  • streamflow is plotted as a blue line,

  • and streamflow manual checkpoints are plotted as black dots.

#format precipitation data for a smooth joining process
precip_daily_join <- precip_daily_clean %>% 
  pivot_wider(
    names_from = "precip_type",
    values_from = "precip_in"
  ) %>% 
  subset(year >= min_year & year <= max_year) %>% 
  rename(precip_10_in = precip_10) %>% 
  mutate(datetime = format(as.POSIXct(date, format = '%Y-%m-%d', 
                                  tz = "GMT"),
                           format = '%Y-%m-%d %H:%M:%S'),
         datetime = as.POSIXct(datetime))

#save as CSV
write.csv(x = precip_daily_join, 
          file = file.path(here("intermediate_data", "precip_daily_join.csv")),
          row.names = FALSE)

#join streamflow and daily precipitation data 
streamflow_precip_daily <- full_join(x = all_streamflow, 
                                     y = precip_daily_join, 
                                     by = "date") %>% 
  select(-precip_in) %>% 
  subset(year >= min_year & year <= max_year)

#calculate the ratio of the 2 y-axes to plot the variables together
trans_value <- max(precip_daily_join$precip_10_in, na.rm = TRUE) / max(all_streamflow$stream_height_ft, na.rm = TRUE)

#plot 
p_daily <- ggplot() + 
  #precipitation data 
  geom_col(data = precip_daily_join, 
            aes(x = datetime, 
                y = precip_10_in,
                group = 1,
                #create hovering labels for interactive graph 
                text = paste0("DateTime: ", datetime, "\n",
                              "Precipitation (in/10): ", precip_10_in)),
            colour = I("grey"),
            size = 0.25) + 
  #streamflow data 
  geom_line(data = all_streamflow,
             aes(x = datetime, 
                 y = stream_height_ft, 
                 group = 1,
                 #create hovering labels for interactive graph 
                 text = paste0("DateTime: ", datetime, "\n",
                              "Stream Height (ft): ", round(stream_height_ft, digits = 3))),
            color = "blue",
            size = 0.4) + 
  #manual check points
  geom_point(data = mc_clean, 
             aes(x = datetime, 
                 y = stripchart_stage, 
                 group = 1,
                 #create hovering labels for interactive graph 
                 text = paste0("DateTime: ", datetime, "\n",
                              "Stream Height Checkpoint (ft): ", stripchart_stage)),
             size = 0.5) + 
  theme_classic() + 
  labs(x = "Time", 
       title = paste0("S2 Bog Streamflow and Cumulative \n Daily Precipitation (", min_year, "-", max_year, ")"),
       subtitle = "Streamflow is plotted in blue. \n Precipitation is plotted in grey. \n Manual streamflow checks are plotted as black points.") + 
  theme(plot.title = element_text(hjust = 0.5),
        plot.subtitle = element_text(hjust = 0.5, 
                                     size = 7)) +
  scale_y_continuous(
    #features of the first axis
    name = "Stream Height (ft)",
    #add a second axis and specify its features
    ##determine the ratio between the max value of Axis 1 vs the max value of Axis 2 to decide what number to put in the trans argument
    ###for example, max value of precipitation / max value of streamflow = 0.533...
    sec.axis = sec_axis(trans = ~.*trans_value, name = "Cumulative Daily Precipitation / 10 (in)")
  )

#static plot
#p_daily

#save the plot in the figures folder 
ggsave(filename = "streamflow_precip_daily_mc.png",
       plot = p_daily,
       path = "figures/",
       width = 8,
       height = 4,
       units = c("in"),
       dpi = 300)

#interactive plot 
ggplotly(p_daily, tooltip = "text")

Code Accessibility

Note that this file is being knit as index.html into the precip_comparisons repository in order to update the GitHub pages website, where the plots can be viewed online.